💃 Cut the wait time 🕺

Good morning, Salesforce Nerds! Imagine this: a sales rep enters a lead in a mobile app while on the road.

Then they wait… and wait… for that lead to show in Salesforce. ⏳️ 

If it takes hundreds of milliseconds or hundreds of seconds, that delay is a jarring rupture in “real time” expectation.

Every millisecond you shave off is a better user experience, faster decision making, and a competitive edge. ⚡️ 

In systems lingo, latency is the time between initiating an action (request) and getting a response. It includes network hops, queuing delays, processing, and I/O delays.

From a Salesforce lens: when your flows, UIs, or external syncs stall, your users feel it. And they hate it. 😡 

Low latency engineering is the art and science of architecting systems so they respond in near real time. Not “next minute.”

TABLE OF CONTENTS

💃 Cut the wait time 🕺

• Core Pillars Of Low Latency

• Architecture Blocks You'll Use

• Example: Shopify -> Salesforce

• Why It Matters To Salesforce Teams

• Conclusion

THE SECRET SAUCE INGREDIENTS

CORE PILLARS OF LOW LATENCY

To build low-latency systems, you lean on a few recurring principles. 📚️ 

Think of them like ingredients in a high-performance recipe.

⤴️ Non-blocking / asynchronous design
Don’t force the UI or transaction to wait on slow operations (e.g. HTTP calls, long-running logic). Use queues, event-driven flows, future/Queueable/Batch Apex, or Platform Events to decouple.

🧠 Caching and memory-first access
Keep frequently accessed data close … in memory or fast-access caches. Multi-layer caching (in-process, distributed) helps. Salesforce uses a multi-layered caching design in its AI inference engine to squeeze out a 400 ms bottleneck to sub-ms performance.

🧩 Optimal data structures & minimal transformations
Use data structures tuned for access (maps, sets) over naive scanning. Avoid unnecessary data copying, serialization, or transformations in the critical path.

🤘 Parallel processing / concurrency
If tasks can run in parallel (independently), do so. Use batch splits, parallel streams, or distribute across nodes.

🎛️ Network and I/O tuning
Minimize round-trips, compress payloads, batch multiple requests, use faster protocols. A network traversal is nontrivial cost.

📊 Profiling, measurement, continuous tuning
You can’t optimize what you don’t measure. Use logs, monitors, APM tools to find hotspots and iterate.

🛡️ Edge / external optimizations
When parts of your system lie in infrastructure you don’t control (CDN, external APIs), use techniques like prefetching, retries, fallback caches, and redundancy to shield your core path.

YOUR BUILDING BLOCKS ON PAPER

ARCHITECTURE BLOCKS YOU’LL USE

Here’s how those principles map to concrete pieces in a Salesforce-centric architecture:

In modern Salesforce environments, Data 360 also layers in high-throughput, low-latency ingestion and indexing for external data sets. 👍️ 

Salesforce engineers have also used micro-batching in data transfer patterns.

Grouping small payloads into slightly larger ones to reduce per-call overhead. 🪣 

WATCH THIS IN ACTION

EXAMPLE: SHOPIFY → SALESFORCE

Let’s walk a scenario:

Your company runs Shopify storefronts and you want every new (or updated) customer synced into Salesforce in near real time.

Naïve design (slow):

1. Shopify webhook triggers your middleware.

2. Middleware does a synchronous call to Salesforce REST API to upsert customer.

3. Salesforce processing includes logic, triggers, and related record updates.

4. Middleware waits for response.

This blocks the workflow, and network delays + API consumption become the bottleneck.

Low-latency redesign:

1. Shopify webhook fires → middleware publishes a message to a queue (e.g. Kafka, Heroku Redis, or Mulesoft queue).

2. A subscriber POSTs a custom event message into a Salesforce object.

3. Within Salesforce, a trigger or Flow listens for that event and enqueues work into Queueable or Batch Apex for heavy processing tasks.

4. Meanwhile, a cache inside the middleware or even in Salesforce (if small) stores salient Shopify data.

5. If the UI or a service needs immediate reference, it reads from cache (fresh enough) and asynchronously finishes the full sync.

In Apex pseudo-style:

// trigger handler on Platform Event
public with sharing class ShopifyEventListener {
  public static void handleEvents(List<ShopifyEvent__e> events) {
    for (ShopifyEvent__e ev :events) {
        System.enqueueJob(
           new SyncJob(
             ev.customerPayload
           )
        );
    }
  }
}

// queueable
public class SyncJob implements Queueable {
  private CustomerPayload payload;

  public SyncJob(CustomerPayload p) { 
     payload = p; 
  }

  public void execute(Context ctx) {
    // do the upsert, cross-object updates, checks
  }
}

You’ve removed the synchronous coupling between Shopify → Salesforce. The mid path is non-blocking, and users aren’t held hostage by external latency. 🤌 

You can improve further by partitioning by region, grouping events, or using parallel consumers. 🔥 

BEYOND BRAGGING RIGHTS

WHY IT MATTERS TO SALESFORCE TEAMS

Low latency isn’t just tech showmanship. ❌ It pays real dividends:

• User satisfaction & adoption — Sales reps, service agents, and customers expect near-immediacy. Stall them, and adoption erodes.

• Business agility — Real-time triggers and flows power features like live credit checks, game-day inventory updates, or dynamic lead routing.

• Competitive edge — In many domains, the first system to respond wins: automated quotes, high-velocity trades, or fast decisioning.

• Scalable resilience — Systems built for low latency tend to be better decoupled, more debug-friendly, and easier to evolve.

• Modern architecture alignment — Salesforce is pushing toward real-time (Data 360, Event-Driven, AI). If your architecture lags, you’ll be playing catch-up.

In short: low latency engineering aligns with the direction Salesforce, and modern enterprise systems, are heading. 👈️ 

WRAPPING THINGS UP

CONCLUSION

Low latency engineering is the architecture mindset and implementation discipline of shrinking every nanosecond you can. 🤏 

From network hops, database access, transformations, and event handovers.

Within a Salesforce-first universe, your levers include Platform Events, CDC, Queueable/Batch Apex, cache layers, smart orchestration, and decoupling via queues.

If you architect your next integration with these principles, you get a system that behaves like magic: actions ripple across your platform almost instantly. 💥 

That’s not just pleasing. It's a difference maker in user trust, throughput, and future scalability. 💯 

So pull out your whiteboard marker, draw your event bus, sketch your cache layer, and treat latency like a nemesis to defeat.

Your users will thank you. 🙏 

SOUL FOOD

Today’s Principle

and now....Salesforce Memes